Handling failures when synchronizing objects during a write operation

ABSTRACT

A method for execution by a dispersed storage network (DSN). The method begins by obtaining a data object for synchronized storage within a plurality of storage vaults, identifying a plurality of storage vaults, encoding the data object for each storage vault, initiating storage of data slices for each storage vault and interpreting received data slice information from at least some of the storage vaults to determine a number of storage vaults that have successfully stored the corresponding plurality of sets of encoded data slices and when the vault threshold number of storage vaults have not successfully stored the corresponding plurality of sets of encoded data slices within a synchronization timeframe, initiating a rollback process to abandon storage of the data object in the plurality of storage vaults and a store data response to indicate unsuccessful synchronized storage of the data object in the plurality of storage vaults.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120, as a continuation-in-part (CIP) of U.S. Utility patentapplication Ser. No. 15/661,332, entitled “SYNCHRONOUSLY STORING DATA INA PLURALITY OF DISPERSED STORAGE NETWORKS,” filed Jul. 27, 2017, whichclaims priority as a continuation-in-part (CIP) of U.S. Utility patentapplication Ser. No. 14/927,446, entitled “SYNCHRONIZING STORAGE OF DATACOPIES IN A DISPERSED STORAGE NETWORK,” filed Oct. 29, 2015, now U.S.Pat. No. 9,727,427, issued on Aug. 8, 2017, which claims prioritypursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No.62/098,449, entitled “SYNCHRONOUSLY STORING DATA IN A PLURALITY OFDISPERSED STORAGE NETWORKS,” filed Dec. 31, 2014, all of which arehereby incorporated herein by reference in their entirety and made partof the present U.S. Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of another dispersed storage network(DSN) that includes a plurality of storage vaults in accordance with thepresent invention; and

FIG. 9A is a flowchart illustrating another example of synchronizingstorage of new data in a plurality of storage vaults.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-9A. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSTN memory 22for a user device, a group of devices, or for public access andestablishes per vault dispersed storage (DS) error encoding parametersfor a vault. The managing unit 18 facilitates storage of DS errorencoding parameters for each vault by updating registry information ofthe DSN 10, where the registry information may be stored in the DSNmemory 22, a computing device 12-16, the managing unit 18, and/or theintegrity processing unit 20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generateper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSTN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

In one embodiment, when a DS processing unit chooses to synchronizeobjects to N vaults during a write operation, the manner in which ithandles and processes errors must be amended (as will be discussed infurther detail in FIGS. 9 and FIG. 9A descriptions below). Normally,when writing to a single vault, if an error is encountered that errorwill cause the operation to fail and the appropriate error message to bereturned to the requester. However, in a configuration where the DSprocessing unit decides to distribute the write operation across somenumber of the N vaults, the manner in which errors are processed andhandled becomes more nuanced. In the case where the DS processing unitis writing to two vaults simultaneously, if the threshold for writing tovaults is 1 and 1 error is encountered, the DS processing unit willsuspend and optionally roll-back the operation to the vault whichencountered the write error, while continuing to process the writeoperation to the other vault which has not yet failed. If the writeoperation succeeds on at least a threshold number of vaults, then the DSprocessing unit will return a success indicator to the requester(optionally indicating the number of vaults on which the operation wascompleted successfully).

If, however, a sufficient number of failures occur across the vaultsthat a threshold cannot be met, the DS processing unit will cancel androllback all operations and return an error indicator to the requester.Since the types of errors may be unique or different, the DS processingunit may return an error response including each of the failures foreach vault where an error was encountered. Or in other cases, where theDS processing unit is constrained to return only a single errorindicator, it may select the one that is most specific, least general,or conveys the greatest amount of information.

FIG. 9 is a schematic block diagram of another dispersed storage network(DSN) that includes a plurality of storage vaults, the network 24 ofFIG. 1, and a distributed storage and task (DST) processing unit 16(computing device) of FIG. 1. The plurality of storage vaults may beimplemented utilizing one or more sets of DST execution (EX) units. Eachset of DST execution units may include any number of DST executionunits. For example, vault 1 is implemented to include a first set of DSTexecution units 1-1 through 1-n, vault 2 is implemented to include asecond set of DST execution units 2-1 through 2-n, etc. through vault Vthat is implemented to include a “Vth” set of DST execution units V-1through V-n. Each DST execution unit may be implemented utilizing a DSTexecution unit (storage unit) 36 of DSN memory 22 as shown in FIG. 1.

The DSN functions to synchronize storage of newly stored data in theplurality of storage vaults. In an example of operation of thesynchronous storage of the data, the DST processing unit 16 receives astore data request 350 from a requesting entity. The store data request350 includes one or more of a data object for storage, metadata of thedata object including one or more of a data identifier a data sizeindicator, an identifier of the requesting entity, a data typeindicator, a data owner identifier, or a synchronization levelindicator. Having received the store data request 350, the DSTprocessing unit 16 identifies the plurality of storage vaults forstorage of the data object. The identifying may be based on one or moreof the metadata of the data object, an interpretation of system registryinformation, a predetermination, or an interpretation of a request. Forexample, the DST processing unit 16 identifies the storage vaults 1-Vbased on the identifier of the requesting entity.

Having identified the plurality of storage vaults, for each storagevault of the plurality of storage vaults, the DST processing unit 16generates a corresponding plurality of sets of encoded data slices 352in accordance with dispersal parameters associated with the storagevault. As a specific example, the DST processing unit 16 obtains thedispersal parameters for the storage vault, and when, the dispersalparameters are unique, dispersed storage error encodes the data objectto produce another plurality of sets of encoded data slices 352.

Having produced the encoded data slices 352, for each storage vault ofthe plurality of storage vaults, the DST processing unit 16 initiatesstorage of the corresponding plurality of sets of encoded data slices.As a specific example, the DST processing unit 16 issues, via thenetwork 24, one or more sets of write slice requests to a set of DSTexecution units associated with the storage vault, where the one or moresets of write slice requests includes the corresponding plurality ofsets of encoded data slices 352. Having sent the encoded data slices tothe plurality of storage vaults for storage, the DST processing unit 16receives, via the network 24, slice information 354 from at least someof the storage vaults. The slice information 354 includes one or more ofa write slice response, a list slice request, a list slice response, aslice name, a slice revision number, a data object revision number, aslice revision number, a rollback write request, or a rollback writeresponse.

Having received the slice information 354, the DST processing unit 16interprets the received slice information 354 to determine how manystorage vaults have successfully stored the corresponding plurality ofsets of encoded data slices. As a specific example, for each storagevault slice information 354, the DST processing unit 16 determineswhether the plurality of sets of encoded data slices 352 have beensuccessfully stored in at least a write threshold number of DSTexecution units associated with the storage vault. For instance, the DSTprocessing unit 16 interprets write slice responses indicating successor failure of storage operations.

When the vault threshold number of storage vaults have not yetsuccessfully stored the corresponding plurality of sets of encoded dataslices within a synchronization timeframe, the DST processing unit 16initiates a rollback process to abandon storing the data object in theplurality of storage vaults. As a specific example, the DST processingunit 16 issues, via the network 24, rollback requests to each storagevault to facilitate deletion of the pluralities of sets of encoded dataslices.

Having issued the rollback request, the DST processing unit 16 generatesa store data response 356 to indicate unsuccessful synchronize storageof the data object in the plurality of storage vaults. As a specificexample, the DST processing unit 16 generates the store data response356 to include an indicator of which storage vaults were unsuccessfuland to include a root cause indicator for the unsuccessful storage. Forinstance, if one error indicated unable_to_communicate, and anothererror indicated invalid_credentials, then the invalid_credentials errorwould be returned to the requesting entity, as it provides more specificinformation about the error condition and about how it might beresolved. As such, each error message may be given a “specificity score”which can be used to evaluate and determine which error indicator to bereturned. Having generated the store data response, the DST processingunit 16 sends the store data response 356 to the requesting entity.

FIG. 9A is a flowchart illustrating another example of synchronizingstorage of new data in a plurality of storage vaults. The methodincludes step 366 where a processing module (e.g., of a distributedstorage and task (DST) processing unit) obtains a data object forsynchronized storage within a plurality of storage vaults. The methodcontinues in step 368, where a processing module identifies theplurality of storage vaults. The method continues in step 370, where aprocessing module encodes the data object for each storage vault toproduce a corresponding plurality of sets of encoded data slices inaccordance with dispersal parameters associated with the storage vault.The method continues in step 372, where a processing module initiatesstorage for each storage vault of the corresponding plurality of sets ofencoded data slices. The method continues in step 374, where aprocessing module interprets received slice information from at leastsome of the storage vaults to determine a number of storage vaults thathave successfully stored the corresponding plurality of sets of encodeddata slices.

When the vault threshold number of storage vaults have not successfullystored the corresponding plurality of sets of encoded data slices withina synchronization timeframe, the method continues at step 386 where theprocessing module initiates a rollback process to abandon storage of thedata object in the plurality of storage vaults. For example, theprocessing module issues rollback requests to each storage vault of aplurality of storage vaults to facilitate deletion of the correspondingplurality of sets of encoded data slices.

The method continues at step 388 where the processing module generates astore data response to indicate unsuccessful synchronized storage of thedata object in the plurality of storage vaults. For example, theprocessing module identifies one or more storage vaults associated withthe unsuccessful storage, and for each, identifies one or more readcauses associated with the unsuccessful storage, generates the storedata response to include the identities of the one or more storagevaults associated with the unsuccessful storage, and, for each storagevault, the identified one or more causes, and sends the store dataresponse to a requesting entity.

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other computing devices. In addition, at least one memorysection (e.g., a non-transitory computer readable storage medium) thatstores operational instructions can, when executed by one or moreprocessing modules of one or more computing devices of the dispersedstorage network (DSN), cause the one or more computing devices toperform any or all of the method steps described above.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processing modules of one or more computing devices of a dispersed storage network (DSN), the method comprises: obtaining a data object for synchronized storage within a plurality of storage vaults; identifying the plurality of storage vaults; encoding the data object for each storage vault of the plurality of storage vaults to produce a corresponding plurality of sets of encoded data slices in accordance with dispersal parameters associated with the storage vault; initiating storage for each storage vault of the corresponding plurality of sets of encoded data slices; interpreting received slice information from at least some of the storage vaults to determine a number of storage vaults that have successfully stored the corresponding plurality of sets of encoded data slices; when a vault threshold number of storage vaults have not successfully stored the corresponding plurality of sets of encoded data slices within a synchronization timeframe, initiating a rollback process to abandon storage of the data object in the plurality of storage vaults; and generating a store data response to indicate unsuccessful synchronized storage of the data object in the plurality of storage vaults.
 2. The method of claim 1, wherein the initiating a rollback process includes issuing rollback requests to each storage vault of the plurality of storage vaults to facilitate deletion of the corresponding plurality of sets of encoded data slices.
 3. The method of claim 1, wherein the store data response includes identities of one or more storage vaults associated with the unsuccessful storage.
 4. The method of claim 3, wherein, for each storage vault the one or more storage vaults, the store data response includes one or more causes associated with the unsuccessful storage.
 5. The method of claim 1, wherein the obtaining includes a store data request including one or more of: a data object for storage, metadata of the data object including one or more of a data identifier a data size indicator, an identifier of a requesting entity, a data type indicator, a data owner identifier, or a synchronization level indicator.
 6. The method of claim 5, wherein the identifier is based on one or more of the metadata of the data object, an interpretation of system registry information, a predetermination, or an interpretation of a request.
 7. The method of claim 1, wherein the identifying includes storage vaults based on an identifier of a requesting entity.
 8. The method of claim 1, wherein unique dispersal parameters encode the data object to produce another plurality of sets of encoded data slices.
 9. The method of claim 1, wherein the initiating storage of the corresponding plurality of sets of encoded data slices includes issuing one or more sets of write slice requests to a set of execution units associated with the storage vault, where the one or more sets of write slice requests includes the corresponding plurality of sets of encoded data slices.
 10. The method of claim 1, wherein the corresponding plurality of sets of encoded data slices include slice information including one or more of: a write slice response, a list slice request, a list slice response, a slice name, a slice revision number, a data object revision number, a slice revision number, a rollback write request, or a rollback write response.
 11. The method of claim 10, wherein, for each storage vault slice information, a processing unit determines whether the plurality of sets of encoded data slices have been successfully stored in at least a write threshold number of execution units associated with the storage vault.
 12. The method of claim 11, wherein the processing unit interprets write slice responses indicating success or failure of storage operations.
 13. The method of claim 1, wherein the generated store data response includes an indicator of which storage vaults were unsuccessful and includes a root cause indicator for the unsuccessful storage.
 14. The method of claim 13, wherein, when two or more indicators are received, a most specific indicator would be returned to a requesting entity to provide more specific information about an error condition and about how it might be resolved.
 15. The method of claim 14, wherein each indicator includes a specificity score that can be used to evaluate and determine which error indicator to be returned.
 16. A computing device of a group of computing devices of a dispersed storage network (DSN), the computing device comprises: an interface; a local memory; and a processing module operably coupled to the interface and the local memory, wherein the processing module functions to: obtain a data object for synchronized storage within a plurality of storage vaults; identify the plurality of storage vaults; encode the data object for each storage vault to produce a corresponding plurality of sets of encoded data slices in accordance with dispersal parameters associated with the storage vault; initiate storage for each storage vault of the corresponding plurality of sets of encoded data slices; interpret received slice information from at least some of the storage vaults to determine a number of storage vaults that have successfully stored the corresponding plurality of sets of encoded data slices; and when a vault threshold number of storage vaults have not successfully stored the corresponding plurality of sets of encoded data slices within a synchronization timeframe, initiate a rollback process to abandon storage of the data object in the plurality of storage vaults; and generate a store data response to indicate unsuccessful synchronized storage of the data object in the plurality of storage vaults.
 17. The computing device of claim 16, wherein the initiate a rollback process includes issuing rollback requests to each storage vault of the plurality of storage vaults to facilitate deletion of the corresponding plurality of sets of encoded data slices.
 18. The computing device of claim 16, wherein the generated store data response includes an indicator of which storage vaults were unsuccessful and includes a root cause indicator for the unsuccessful storage.
 19. The computing device of claim 18, wherein, when two or more indicators are received, a most specific indicator would be returned to a requesting entity to provide more specific information about an error condition and about how it might be resolved.
 20. The computing device of claim 19, wherein each indicator includes a specificity score that can be used to evaluate and determine which error indicator to be returned. 